They contend that the ranks of today’s most valuable companies are increasing populated with those that successfully build and control platforms. Think Apple with iTunes, John Deere with its My John Deere Operations Center, and a host of other platform-based companies as diverse as McCormick Foods, Amazon, and Uber.

The problem with platforms is context. The authors think platform-based businesses eventually will come to dominate every industry, but they caution readers that the window of opportunity for launching a successful platform will vary according to the characteristics of a specific industry.

How do you know if and when your industry is ripe for platform disruption? As this excerpt from the forthcoming book (reprinted with permission) details, the emergence of platform businesses is most likely in highly-fragmented industries with non-scalable gatekeepers in which information is both a significant source of value and extremely asymmetrical. The emergence of platform disruption is less likely in resource-intensive industries that are subject to high levels of regulatory control and high failure costs.

Adapted excerpt from chapter 12 of

Platform Revolution: How Networked Markets Are Transforming the Economy and How to Make Them Work for You

By Geoffrey Parker, Marshall Van Alstyne and Sangeet Paul Choudary

To be published by W.W. Norton on March 28, 2016

What Makes an Industry Ready for the Platform Revolution?

In our research into the disruption of industries by platforms, we’ve noted characteristics that make a particular industry especially susceptible. Here are some of the types of businesses that are most likely to join the platform revolution in the years to come:

Information-intensive industries. In most industries today, information is an important source of value—but the more crucial information is as a value source, the closer the industry is to being transformed by platforms. This explains why media and telecom are two of the industries that have already been disrupted so thoroughly by platforms. New entrants have created ecosystems that can create and disrupt content and software more quickly and easily than large firms with thousands of employees once did.

Industries with non-scalable gatekeepers. Retailing and publishing are two examples of industries that traditionally have employed expensive, non-scalable human gatekeepers—buyers and inventory managers in the case of retail, editors in the case of publishing. Both are already undergoing disruption thanks to the rise of digital platforms, with millions of producers (artisans, craftspeople, writers) creating and marketing their own goods through platforms like Etsy, eBay, and Amazon.

Highly fragmented industries. Market aggregation through a platform increases efficiencies and reduces search costs for businesses and individuals looking for goods and services created by far-flung local producers. Platforms ranging from Yelp and OpenTable to Etsy, Uber, and Airbnb have made it easy for customers to visit a single source to gain access to thousands of small suppliers.

Industries characterized by extreme information asymmetries. Economic theory suggests that fair, efficient markets require that all participants have equal access to information about goods, services, prices, and other crucial variables. But in many traditional markets, one set of participants has far better access than others. Used car dealers, for example, knew much more about the condition and history of the cars they sold, as well as about supply and demand variables, than their customers—hence the distrust in which they were held. Data aggregating and sharing platforms such as Carfax are now leveling the field, making detailed information about used car values available to anyone willing to pay a small fee. Other markets where information asymmetries have made fair dealing difficult, from health insurance to home mortgages, are ripe for similar changes.

Based on the factors above, one may question why banking, health care, and education continue to be so resistant to transformation. All three industries are information-intensive. (Health care may seem like a service-intensive industry, but all of its efficiencies are powered by information.) However, industries that might seem to be susceptible to platform approaches, yet are likely to be resistant to such disruption, have certain other characteristics. These include the following:

Industries with high regulatory control. Banking, health care, and education are all highly regulated. Regulations favor incumbents and work against the interests of startups trying to unlock new sources of value. Emerging platforms are starting to attack this problem in an effort to create new sources of value, but regulatory control is holding them back.

Industries with high failure costs. The costs of a defaulted loan or matching a patient with the wrong doctor are much higher than the cost of showing inappropriate content on a media platform. Consumers are reluctant to participate on platforms when the perceived costs of failure are high.

Resource-intensive industries. Resource-intensive industries have typically not been dramatically affected by the Internet. Winning participants in these markets still depend on their access to resources and their ability to manage efficient, large-scale processes such as mining, oil and gas exploration, and agriculture, in which information has a limited role to play.

The impact of these factors will change over time. As more and more processes and tools get connected to the Internet, every industry has the potential to become an information-intensive industry. For example, resource-intensive industries like mining and energy will increasingly need to leverage the power of platforms, creating efficiency gains and faster learning by connecting their resources— material, labor, and machines—over a central network to coordinate workflows. Over the next few years, we will see the start of transformation in large resource-intensive companies as they leverage plat- forms toward greater efficiency gains.

Even as we consider the relative likelihood that various industries will be susceptible to platform transformation in the near future, let’s bear in mind that industry boundaries are becoming increasingly porous due to the impact of platforms. Think about the advertising industry, for example. In a world of pipelines, businesses’ access to consumers was limited to media and retail channels: television net- works, newspapers and magazines, department stores. Very few businesses could afford to own their own direct-to-consumer channels for promoting their goods and services. By contrast, in today’s world of Internet-powered platforms, any business can engage with consumers directly, capturing data about their preferences, connecting them with external producers, and offering personalized services that pro- vide individual customers with unique value.

In effect, every company can now be an advertising company. Uber, for example, has the potential to be the world’s largest hyper- local advertising business. Through its rider data, Uber can gain unique insight into where users live, where they work, when and how often they commute, and many other such aspects of behavior. The company could use such data to connect users with local merchants. Many other kinds of companies with vibrant platforms, from banks to retailers, could employ a similar strategy.

The power of the platform is modifying—even erasing—many other, similar barriers that once separated industries from one another. Thus, one of the most dramatic effects of the rise of the platform has been the emergence of unexpected new competitors from seemingly unrelated industry sectors. Bear this in mind as you consider the possible future impact of the platform model on your own industry, whatever it may be.

Wearables enable and incentivize employee fitness: Amgen, DaVita HealthCare Partners, and Lockton are offering Apple watches to their employees for $25, reports Rachel Emma Silverman in an article in The Wall Street Journal (subscription required). Oh yea, there’s also some fine print: For two years, participating employees must either meet monthly fitness goals (tracked on the watch) or they pay cash for the watch in installments.

The companies are participating in a program conceived by Vitality Group, which also manages and monitors it. The payoff for employees is enhanced fitness and a cool device. Employers should benefit from lower healthcare benefit costs. (And Apple, which is not a partner in the program, sells a bunch of watches.)

Vitality says there are already 17,000 participants in the program in South Africa. The early results: “Vitality members using Apple Watch increased their average weekly physical activity by 96% after joining.”

Optimizing distribution networks with big data analytics: Most corporate supply and distribution chains are siloed, piecemeal, inefficient networks, writes a team at The Boston Consulting Group in a new article. The problem with optimizing them is complexity: A company can easily have a network consisting of more than 500 nodes — plants, clients, transloading locations, and warehouses — and as many as 100,000 arcs — ways to move between the nodes. “To optimize such a network, a company would have to analyze as many as 100 billion possible combinations,” calculate the authors.

The solution, of course, is big data analytics. But before you can put them to work, the authors say you need to do three things: First, pull together all the stakeholders to map the locations of the business’s suppliers, clients, plants, warehouses, DCs, and modes. Second, identify the cost drivers, “including particular modes of transportation, inventory in transit, and specific types of equipment,” and constraints, “such as lead time obligations to clients and production capacities of various plants.” Third, bring in a team of logistics and modeling experts to build, test, and tune a network optimization tool.